We can help you design and deliver an exceptional demand forecasting process.
The need for forecasting
Demand forecasting is a critical business requirement to support a range of business functions, including logistics, production and finance. It is only with an agreed and considered forecast that functions can adequately plan capacity, inventory, labour and cash-flow.
The challenges of forecasting
When forecasting demand, it is key that all elements that can impact sales are identified, assessed and incorporated. Consequently, demand forecasting is not only a statistical exercise, but also requires cross-functional input from teams including sales, supply chain, finance and production.
Many businesses fail to have a cross-functional forecasting process, and often rely only on statistics. This can lead to a lack of business confidence in the forecast and it is not uncommon to find different departments developing their own isolated forecasts; sales, supply chain, production and finance will often see the future very differently!
Who we work with
HERE TO HELP
Next level demand forecasting
A good demand forecast can only be the result of a good demand forecasting process. That process needs to be fast and dynamic for all participating functions, and it needs to have cross-functional consensus.
The first step needs to be a statistical ‘baseline’ expectation which is then passed through each department for sense-checking and input. Varying additions or constraints may need to be applied, including marketing promotions, production capacities, logistics capacities, supplier issues and inventory constraints.
Depending on client requirements we can take several approaches to developing a demand forecast.
Example forecasting development approach
Step 1: Hypothesis Definition
Defining the hypothesis for future sales demand is an important first step. The hypothesis is likely to be formed from a strategic intention alongside suppositions on the economic environment, market opportunity and competitor performance.
With the hypothesis defined, further consideration can then be given to what data will need to be collected to prove/disprove the supposition. This may take the form of tracking sales calls made, volume demanded by targets, sales executives’ perceived probability of success, conversion rates into actual sales, forecasting of future demand from new clients, or tracking how that forecast compares to quantity actually demanded.
Step 2: Tracking templates
At Step 2, our consulting team will convert the business hypothesis and supporting assumptions that were generated into a mathematical model, and will design a data capture process with templates. The templates will incorporate automatic data validation as well as useful dynamic dashboards for the stakeholders to observe.
Additionally, a consolidation tool to collate the data being tracked can be created, allowing for easy assimilation of data points.
Step 3: Hypothesis testing
Using the Data Tracking Templates from Step 2, our demand forecasting consultants will test the validity of the hypothesis as data develops, and potentially collect alternative data in the event of early detection of variances.
Any data or useful insights that could be used to help the sales team will be passed on, and additionally, dashboard reporting of performance on a monthly basis will be generated, so that different approaches can be compared and used for performance evaluation / improving sales techniques.
Step 4: Prediction Interval
A scenario analysis will be run to assign probabilities to various events that could impact sales levels on the mid-to-long term horizon. Typical event variables could include substitute products causing a change in equilibrium on the supply-demand curves or regional economic conditions resulting in a shock to aggregate demand.
The outputs from this scenario analysis will be run through a Monte Carlo simulation in order to generate a prediction interval for the baseline forecast, within which it is likely future sales will fall.
Step 5: Tool Development
Our consulting team will, using the models and the data from the preceding four steps, design an easy to use forecasting tool to allow the client to continue tracking and forecasting sales independently.
Where deep integration of forecasting tools may be required with a clients ERP system, or integration with MRP functionality, then the consultants can support system selection and process implementation as the concluding steps.
Forecasting articles & advice
Snap – the umbrella organisation which includes the Snapchat social media platform – launched the Snap Spectacles in 2016. This was their first foray into
Get in touch!
Hello! I’m Tamsin, Client Services Coordinator at Paul Trudgian. Please get in touch by phone, email or the contact form and I’ll make sure your enquiry is dealt with promptly and passed to the right member of the consulting team. We look forward to hearing from you!